Evaluating Pareto optimal tradeoffs for hippocampal avoidance whole brain radiotherapy with knowledge-based...

The goal of this study is to investigate the Pareto optimal tradeoffs between target coverage and hippocampal sparing using knowledge-based multicriteria optimization (MCO). Ten prior clinical cases were selected that were treated with hippocampal avoidance whole brain radiotherapy (HA-WBRT) using VMAT. A new, balanced plan was generated for each case using an in-house RapidPlan model in the Eclipse V16.1 treatment planning system. The MCO decision support tool was used to create 4 Pareto optimal plans. The Pareto optimal plans were created using PTV D_min and hippocampus D_max as tradeoff criteria. The tradeoff plans were generated for each patient by adjusting PTV D_min from the value achieved by the corresponding balanced plan in fixed intervals as follows: -4 Gy, -2 Gy, +2 Gy, and +4 Gy. All plans were normalized so that 95% of the PTV was covered by the prescription dose. A 1-way ANOVA, with Geisser-Greenhouse correction, was used for statistical analysis. When evaluating the achieved PTV D_min and D_98%, the results showed the dose to the hippocampus decreased as coverage lowered and in comparison, D_98% was higher when the PTV coverage was increased. When comparing multiple tradeoffs, the p-value for PTV D_98% was 0.0026, and the p-values for PTV D_2%, PTV D_min, Hippocampus D_max, D_min, and D_mean were all less than 0.0001, indicating that the tradeoff plans achieved statistically significant differences. The results also showed that Pareto optimal plans failed to reduce hippocampal dose beyond a certain point, indicating more limited achievability of the MCO-navigated plans than the interface suggested. This study presents valuable data for planning results for HA-WBRT using MCO. MCO has shown to be mostly effective in adjusting the tradeoff between PTV coverage and hippocampal dose.